Popular GitHub Repositories for Pre

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.

Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)

The official GitHub page for the survey paper "A Survey of Large Language Models".

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

A collection of pre-trained, state-of-the-art models in the ONNX format

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022

Silero VAD: pre-trained enterprise-grade Voice Activity Detector

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js

Data processing for and with foundation models! ? ? ? ?? ??? ? ?

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

An Open-Source Framework for Prompt-Learning.

Pre-trained Deep Learning models and demos (high quality and extremely fast)

Must-read papers on prompt-based tuning for pre-trained language models.